Open AccessSystematization of approaches to assessing the quality of spatio-temporal knowledge sources
Author(s) -
Sergey Savosin,
Sergey Mikhailov,
Nikolay Teslya
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1801/1/012006
Subject(s) - computer science , quality (philosophy) , relevance (law) , scope (computer science) , crowdsourcing , rank (graph theory) , domain knowledge , domain (mathematical analysis) , permission , data science , information retrieval , data mining , knowledge management , world wide web , mathematics , mathematical analysis , philosophy , epistemology , combinatorics , political science , law , programming language
There are two main ways of creating and filling spatio-temporal knowledge bases: by professional cartographers and by volunteers using the crowdsourcing concept. The knowledge provided by professionals is highly accurate, but narrow in scope and domain-specific, as well as rarely updated. Editing of this kind of sources is impossible without permission, which makes them closed, despite the possibility of free use of the knowledge itself. On the opposite, ordinary users can provide a large amount of information in various fields of knowledge with minimal delay. However, the quality of such information and its accuracy will differ depending on the subject area and external factors, such as the accuracy of user devices sensors, the distribution of users in the area, etc. The integration of knowledge from various sources will increase the overall accuracy and relevance of the data provided, which can be used to increase quality of decision making. Automatic integration requires the development of methods for estimating quality of knowledge sources, to rank them and choose only those that can provide sufficient quality in the criteria of the problem being solved. This paper presents a systematization of existing approaches to assessing sources of knowledge and, in particular, spatio-temporal knowledge.